Papers Emotion Detection and Classification
“Emotion Detection and Classification” 태그가 달린 논문 5편 · 필터 해제
Expansion Quantization Network: An Efficient Micro-emotion Annotation and Detection Framework
Text emotion detection constitutes a crucial foundation for advancing artificial intelligence from basic comprehension to the exploration of emotional reasoning. Most existing emotion detection datasets rely on manual an…
Emotion Detection and ClassificationQuantizationAttention-based Modeling for Emotion Detection and Classification in Textual Conversations
This paper addresses the problem of modeling textual conversations and detecting emotions. Our proposed model makes use of 1) deep transfer learning rather than the classical shallow methods of word embedding; 2) self-at…
Emotion Detection and ClassificationEmotion Recognition in ConversationGeneral ClassificationTransfer LearningLIRMM-Advanse at SemEval-2019 Task 3: Attentive Conversation Modeling for Emotion Detection and Classification
This paper addresses the problem of modeling textual conversations and detecting emotions. Our proposed model makes use of 1) deep transfer learning rather than the classical shallow methods of word embedding; 2) self-at…
Emotion Detection and ClassificationGeneral ClassificationTransfer LearningEmotion Detection and Classification in a Multigenre Corpus with Joint Multi-Task Deep Learning
Detection and classification of emotion categories expressed by a sentence is a challenging task due to subjectivity of emotion. To date, most of the models are trained and evaluated on single genre and when used to pred…
Emotion Detection and ClassificationGeneral ClassificationMulti-Task LearningSentenceAnnotating Events in an Emotion Corpus
This paper presents the development of a Chinese event-based emotion corpus. It specifically describes the corpus design, collection and annotation. The proposed annotation scheme provides a consistent way of identifying…
Emotion Detection and Classification